ATL8 Antibody

What is ATL8 and why are antibodies against it important for plant research?

ATL8 is a plant-specific RING-type ubiquitin ligase belonging to the Arabidopsis Tóxicos en Levadura (ATL) family, which currently comprises 91 identified isoforms in the Arabidopsis genome . This membrane-localized protein plays a crucial role in plants' adaptation to sugar starvation stress, with its expression significantly increasing under extended darkness or sugar deprivation conditions and decreasing rapidly when exogenous sugar is supplied .

Antibodies against ATL8 are essential tools that enable researchers to:

• Track protein abundance during stress responses

• Investigate subcellular localization through immunohistochemistry

• Identify protein interaction partners through co-immunoprecipitation

• Study the regulatory mechanisms governing protein degradation pathways

Recent research has identified Starch Synthase 4 as a putative interaction partner of ATL8, suggesting its involvement in regulating starch accumulation based on sugar availability . Antibodies provide a direct means of validating such interactions and exploring their functional significance in plant physiology.

How does ATL8 structure inform antibody design and experimental applications?

Understanding ATL8's structural features is critical for developing effective antibodies and experimental approaches. ATL8 contains:

• A single transmembrane-like hydrophobic amino acid region (residues 31-53) at its N-terminus

• A RING-H2 type zinc finger domain in its middle portion

• A conserved cysteine residue (C123) essential for ubiquitin ligase activity

These structural characteristics create specific challenges and opportunities for antibody production and application:

• The N-terminal hydrophobic region presents difficulties for recombinant protein expression, often necessitating its exclusion when producing immunogens .

• The highly conserved RING domain may lead to cross-reactivity with other ATL family members, requiring careful epitope selection to ensure specificity.

• For functional studies, antibodies targeting the RING domain may interfere with ubiquitin ligase activity, which can be either a limitation or a useful tool depending on the experimental goals.

• When designing constructs for recombinant protein production as immunogens, researchers have successfully used ATL8 fragments beginning from residue 71 (valine) to ensure proper expression .

• For antibody validation, the catalytically inactive ATL8C123S mutant provides an excellent control to distinguish between functional and structural recognition .

What experimental controls are essential when validating ATL8 antibody specificity?

Proper validation of ATL8 antibodies requires rigorous controls to ensure specificity, particularly given the existence of 91 ATL family members in Arabidopsis with potential structural similarities . Essential validation steps include:

• Genetic controls:

  • Testing against ATL8 knockout or knockdown plant lines

  • Comparing signal in wild-type versus ATL8 overexpression lines

  • Using plant material subjected to conditions known to upregulate (extended darkness) or downregulate (exogenous sugar) ATL8 expression

• Biochemical controls:

  • Pre-absorption with recombinant ATL8 protein to eliminate specific binding

  • Testing against closely related ATL proteins, particularly ATL80 which belongs to the same group K ATL family

  • Peptide competition assays using the immunizing antigen

• Technical controls:

  • Testing antibodies against recombinant wild-type ATL8 and the inactive ATL8C123S mutant

  • Including negative controls (secondary antibody only, pre-immune serum)

  • Using multiple antibodies targeting different epitopes of ATL8

• Analytical validation:

  • Confirming a single band of expected molecular weight in Western blots

  • Verifying subcellular localization matches the expected membrane compartment pattern

  • Conducting immunoprecipitation followed by mass spectrometry to confirm target identity

What techniques are most effective for detecting ATL8 expression patterns during sugar starvation?

Researchers investigating ATL8 expression during sugar starvation can employ several complementary techniques:

• RT-PCR analysis:

  • Allows detection of significant ATL8 expression increases within 4 hours of extended darkness

  • Can demonstrate continuous expression during prolonged dark treatment

  • Shows dramatic reduction within 1 hour of exogenous sucrose application

  • Enables comparison with other sugar-responsive genes

• Western blot analysis:

  • Requires careful membrane protein extraction protocols

  • Benefits from comparison between wild-type and mutant plants

  • Should include appropriate controls for equal loading

  • Can demonstrate protein-level regulation that may differ from transcript patterns

• Immunolocalization:

  • Enables visualization of subcellular distribution in membrane-bound compartments

  • Can be combined with markers for specific organelles to determine precise localization

  • Allows detection of potential relocalization under stress conditions

  • Requires careful fixation protocols to preserve membrane protein epitopes

• Fluorescent protein fusion approaches:

  • Complement antibody-based detection with ATL8-GFP fusions

  • Enable live-cell imaging of protein dynamics

  • The catalytically inactive ATL8C123S variant fused to GFP provides a stabilized form for localization studies

  • Co-expression with markers like FLS2-mCherry helps confirm membrane localization

These methods have revealed that ATL8 expression is primarily regulated by cellular sugar availability rather than light signaling pathways, as demonstrated by the absence of increased expression during extended darkness when exogenous sucrose is present .

How can researchers effectively study ATL8 ubiquitin ligase activity in vitro?

Studying the ubiquitin ligase activity of ATL8 requires specific methodological approaches:

• Recombinant protein production:

  • Remove the N-terminal hydrophobic region and basic regions that inhibit expression

  • Use residues 71-185 fused to a solubility tag like maltose binding protein (MBP)

  • Express in E. coli under optimized conditions

  • Purify using affinity chromatography followed by size exclusion chromatography

• In vitro ubiquitination assay setup:

  • Include purified E1 (ubiquitin-activating enzyme)

  • Add appropriate E2 (ubiquitin-conjugating enzyme)

  • Provide ubiquitin and ATP

  • Incubate at physiological temperature (typically 30°C for plant proteins)

• Detection and analysis:

  • Use Western blotting with anti-ubiquitin antibodies to detect ubiquitinated products

  • Look for heterogeneous higher molecular weight bands indicating ubiquitination

  • Include time course analysis (0, 30, 120 minutes) to monitor reaction progression

  • Compare wild-type ATL8 activity with the catalytically inactive ATL8C123S mutant

• Substrate-specific assays:

  • Include purified potential substrates like Starch Synthase 4

  • Detect substrate-specific ubiquitination using antibodies against the substrate

  • Analyze ubiquitination patterns (mono- vs. poly-ubiquitination)

  • Determine ubiquitin chain linkage types using linkage-specific antibodies

This approach has successfully demonstrated that ATL8 possesses RING-type ubiquitin ligase activity in vitro, which is abolished when the conserved cysteine residue (C123) is mutated to serine .

What approaches are most effective for identifying and validating ATL8 protein interactions?

Identifying and validating protein interactions with ATL8 requires multiple complementary approaches:

• Co-immunoprecipitation with mass spectrometry:

  • Use anti-GFP beads to pull down ATL8C123S-GFP from transgenic plants

  • Include wild-type plants as negative controls

  • Analyze precipitated proteins by mass spectrometry

  • This approach identified Starch Synthase 4 (SS4) as a candidate ATL8 interactor

• Targeted co-immunoprecipitation:

  • Use antibodies against ATL8 to pull down potential interaction partners

  • Alternatively, use antibodies against suspected partners to co-precipitate ATL8

  • Confirm interactions by Western blotting

  • Include appropriate negative controls (pre-immune serum, unrelated antibodies)

• Bimolecular Fluorescence Complementation (BiFC):

  • Fuse ATL8 to one half of a split fluorescent protein

  • Fuse candidate interactors to the complementary half

  • Co-express in plant cells and observe for reconstituted fluorescence

  • Include appropriate controls with non-interacting proteins

• Yeast two-hybrid assays:

  • Use membrane-based yeast two-hybrid systems suitable for membrane proteins

  • Create constructs lacking the transmembrane domain for conventional Y2H

  • Screen against cDNA libraries or test specific candidate interactions

  • Validate positive interactions in planta using methods above

• Protein modification analysis:

  • Determine if ATL8 ubiquitinates identified interactors

  • Monitor stability of interacting proteins in wild-type vs. ATL8 mutant plants

  • Assess whether interactions are regulated by sugar availability

  • Investigate co-localization during stress conditions

These approaches should be applied iteratively, with initial identification of candidates followed by validation through multiple independent methods.

How can researchers use ATL8 antibodies to investigate the relationship between sugar starvation and protein degradation pathways?

ATL8 antibodies enable sophisticated investigations into how sugar starvation triggers selective protein degradation:

• Temporal analysis of protein degradation:

  • Track ATL8 protein levels alongside potential substrates during sugar starvation

  • Monitor ubiquitination status of target proteins using anti-ubiquitin antibodies

  • Measure protein half-lives in wild-type versus ATL8 mutant plants

  • Create time-course profiles under different sugar deprivation regimes

• Regulatory pathway investigation:

  • Use phospho-specific antibodies to monitor SnRK1 activation alongside ATL8 expression

  • SnRK1 knockdown mutants show reduced ATL8 expression, suggesting this energy sensor acts upstream of ATL8

  • Investigate how ATL8 interacts with other components of energy sensing pathways

  • Examine relationships with autophagy and proteasomal degradation systems

• Organelle-specific degradation analysis:

  • Use subcellular fractionation followed by immunoblotting

  • Compare degradation patterns in different cellular compartments

  • Study co-localization of ATL8 with substrate proteins during starvation

  • Investigate whether ATL8 mediates organelle-specific protein quality control

• Metabolic impact assessment:

  • Correlate ATL8 expression with changes in starch metabolism

  • Monitor the relationship with branched-chain amino acid (BCAA) catabolism enzymes

  • ATL8 expression is highly coordinated with genes involved in BCAA degradation (IVD, BCE2/DIN3, DIN4, MCCB)

  • Investigate how these coordinated pathways contribute to maintaining electron flow to the respiratory chain during sugar limitation

What experimental design is recommended for investigating ATL8's role in regulating starch synthesis during energy stress?

The identification of Starch Synthase 4 (SS4) as a putative ATL8 interactor suggests a direct role in modulating starch accumulation in response to sugar availability . A comprehensive experimental design to investigate this relationship would include:

• Protein interaction verification:

  • Confirm ATL8-SS4 interaction using reciprocal co-immunoprecipitation

  • Determine domains responsible for interaction using truncation mutants

  • Investigate whether interaction is regulated by sugar availability

  • Use fluorescence resonance energy transfer (FRET) to quantify interaction dynamics

• Functional relationship characterization:

  • Generate single and double mutants of ATL8 and SS4

  • Measure starch content under normal and sugar starvation conditions

  • Analyze SS4 protein levels and stability in wild-type versus ATL8 mutant plants

  • Determine if ATL8 ubiquitinates SS4 in vitro and in vivo

• Temporal and spatial analysis:

  • Monitor co-localization of ATL8 and SS4 during light/dark transitions

  • Track protein dynamics during extended darkness using time-course immunoblotting

  • Investigate tissue-specific interactions in different plant organs

  • Analyze chloroplast morphology and starch granule formation

• Physiological relevance assessment:

  • Measure survival rates during extended darkness in wild-type versus mutant plants

  • Analyze carbon allocation and utilization patterns during energy stress

  • Investigate recovery dynamics when sugar becomes available after starvation

  • Examine starch degradation rates and patterns

• Integration with energy sensing pathways:

  • Determine how SnRK1 signaling affects the ATL8-SS4 interaction

  • Investigate coordination with trehalose-6-phosphate signaling

  • Analyze transcriptional coordination with other starch metabolism genes

  • Study potential feedback mechanisms regulating ATL8 expression based on starch status

How can ATL8 antibodies be used to investigate cross-talk between sugar starvation and other stress response pathways?

ATL8 antibodies provide valuable tools for exploring how sugar starvation response integrates with other stress signaling networks:

• Combined stress experiments:

  • Subject plants to sugar starvation plus additional stresses (cold, drought, salt)

  • Use immunoblotting to monitor ATL8 protein levels under combined stresses

  • Compare with related ATL family members like ATL80 (involved in phosphate mobilization and cold stress)

  • Investigate stress-specific post-translational modifications

• Hormone response integration:

  • Analyze how plant hormones affect ATL8 expression and localization

  • Study ATL8 regulation in hormone signaling mutants

  • Explore co-immunoprecipitation to identify hormone-dependent interaction partners

  • Investigate whether hormone treatments alter ATL8's ubiquitin ligase activity

• Signaling pathway cross-regulation:

  • Use phospho-specific antibodies to monitor energy sensors (SnRK1) alongside stress-activated protein kinases

  • Analyze whether stress-responsive transcription factors bind to the ATL8 promoter

  • Study how alternative stress-induced membrane modifications affect ATL8 localization

  • Determine if ATL8 substrates change under different stress combinations

• Multi-omics integration:

  • Correlate ATL8 protein levels with transcriptome changes during combined stresses

  • Analyze the ubiquitinome in wild-type versus ATL8 mutant plants under different stresses

  • Study metabolome adjustments focusing on carbon allocation and amino acid metabolism

  • Develop network models of ATL8's position within integrated stress response systems

This approach reveals how ATL8 functions within the broader context of plant stress adaptation mechanisms, potentially identifying convergence points where multiple stress responses are coordinated through targeted protein degradation.

What are common technical challenges when using ATL8 antibodies and how can they be addressed?

Researchers working with ATL8 antibodies frequently encounter several technical challenges:

• Low signal intensity in Western blots:

  • Problem: ATL8 is expressed at low levels under normal conditions

  • Solution: Use extended darkness treatment (4+ hours) to induce expression

  • Problem: Inefficient extraction of membrane-bound ATL8

  • Solution: Use specialized membrane protein extraction buffers with appropriate detergents

• High background in immunolocalization:

  • Problem: Non-specific binding to membranes

  • Solution: Optimize blocking conditions (BSA vs. milk, concentration, duration)

  • Problem: Plant tissue autofluorescence

  • Solution: Use appropriate filters and fluorophores with emission spectra distinct from autofluorescence

• Cross-reactivity with other ATL family members:

  • Problem: Antibodies detecting related ATL proteins

  • Solution: Pre-absorb antibodies with recombinant proteins of closely related ATLs

  • Problem: Difficulty distinguishing specific signal

  • Solution: Include ATL8 knockout/knockdown plants as negative controls

• Inconsistent immunoprecipitation results:

  • Problem: Transient protein interactions difficult to capture

  • Solution: Use crosslinking agents to stabilize interactions before lysis

  • Problem: Low protein recovery

  • Solution: Use the catalytically inactive ATL8C123S mutant which may form more stable complexes

• Variable results between experiments:

  • Problem: Antibody batch-to-batch variation

  • Solution: Validate each new antibody lot against standard samples

  • Problem: Environmental factors affecting ATL8 expression

  • Solution: Strictly control growth conditions and sugar availability

How can researchers optimize immunohistochemistry protocols for membrane-localized ATL8?

Optimizing immunohistochemistry for membrane-localized proteins like ATL8 requires specific protocol adjustments:

• Fixation optimization:

  • Test multiple fixatives (paraformaldehyde, glutaraldehyde, combinations)

  • Evaluate different fixation durations (30 minutes to overnight)

  • Consider mild fixation to preserve membrane protein epitopes

  • Test with and without vacuum infiltration for better fixative penetration

• Membrane permeabilization:

  • Use detergents appropriate for membrane proteins (Triton X-100, Tween-20, saponin)

  • Test concentration gradients to determine optimal permeabilization

  • Consider detergent-free methods using freeze-thaw cycles for certain applications

  • Evaluate enzymatic digestion of cell walls for improved antibody accessibility

• Antigen retrieval methods:

  • Test heat-induced epitope retrieval at various pH conditions

  • Evaluate proteolytic retrieval methods (proteinase K, trypsin)

  • Consider sodium citrate buffer treatment

  • Compare microwave, pressure cooker, and water bath methods

• Signal amplification strategies:

  • Use biotin-streptavidin systems for signal enhancement

  • Consider tyramide signal amplification for low-abundance proteins

  • Test polymer-based detection systems

  • Evaluate quantum dot conjugates for improved signal-to-noise ratio

• Controls and validation:

  • Include wild-type versus ATL8 mutant tissue sections

  • Compare with GFP-tagged ATL8 localization patterns

  • Perform peptide competition controls

  • Include secondary-only controls to assess non-specific binding

These optimizations help ensure specific detection of membrane-localized ATL8 while minimizing background and preserving tissue morphology.

What methodological approaches can address the challenge of detecting transient ATL8-substrate interactions?

The dynamic and often transient nature of ubiquitin ligase-substrate interactions presents challenges for studying ATL8's biological targets:

• Stabilization of interactions:

  • Use catalytically inactive ATL8C123S mutant which forms more stable complexes with substrates

  • Apply reversible crosslinking before cell lysis (formaldehyde, DSP, DTBP)

  • Treat samples with proteasome inhibitors to prevent substrate degradation

  • Consider 26S proteasome mutants to stabilize ubiquitinated intermediates

• Proximity-based labeling approaches:

  • Fuse ATL8 to biotin ligase (BioID) or engineered peroxidase (APEX)

  • Allow in vivo biotinylation of proximal proteins

  • Purify biotinylated proteins and identify by mass spectrometry

  • Compare labeling patterns between wild-type ATL8 and ATL8C123S

• Synchronized induction systems:

  • Create inducible ATL8 expression systems

  • Apply sugar starvation conditions in a controlled time course

  • Capture early interaction events before substrate degradation

  • Perform time-resolved interaction proteomics

• Computational prediction and targeted validation:

  • Use bioinformatics to predict potential ATL8 substrates based on degron motifs

  • Screen candidates systematically using co-immunoprecipitation

  • Validate with in vitro ubiquitination assays

  • Confirm physiological relevance through genetic approaches

• Specialized co-immunoprecipitation protocols:

  • Use tandem affinity purification with stringent washing

  • Include detergents optimized for membrane protein interactions

  • Apply TUBE (Tandem Ubiquitin Binding Entities) technology to capture ubiquitinated substrates

  • Consider on-bead digestion followed by mass spectrometry to minimize sample manipulation

These approaches help overcome the inherent challenges of studying enzyme-substrate interactions that are both transient and often lead to substrate degradation.

What statistical approaches are most appropriate for analyzing immunoblot data in ATL8 research?

• Quantification methodology:

  • Use densitometry software with appropriate background subtraction

  • Measure integrated density rather than peak intensity

  • Establish standard curves using recombinant protein dilutions

  • Normalize to appropriate loading controls (total protein stains preferred over housekeeping proteins)

• Experimental design considerations:

  • Include at least three biological replicates per condition

  • Analyze technical replicates to assess method variability

  • Use randomized blot loading patterns to avoid edge effects

  • Include positive and negative controls on each blot

• Statistical tests for comparative studies:

  • Apply ANOVA for comparing multiple conditions

  • Use appropriate post-hoc tests (Tukey's, Bonferroni, Dunnett's)

  • Consider non-parametric alternatives if normality assumptions are violated

  • Perform power analysis to ensure adequate sample size

• Time-course analysis approaches:

  • Apply repeated measures ANOVA for within-subject designs

  • Consider curve-fitting for expression kinetics

  • Use area under curve (AUC) calculations for cumulative response

  • Apply time series analysis for complex temporal patterns

How should researchers distinguish between ATL8-specific signals and potential artifacts in immunohistochemistry?

Distinguishing genuine ATL8 signals from artifacts in immunohistochemistry requires systematic validation and controls:

• Essential controls for signal validation:

  • Genetic controls: Compare wild-type with ATL8 knockout/knockdown tissues

  • Antibody controls: Pre-immune serum, isotype controls, secondary-only controls

  • Peptide competition: Pre-absorb antibody with immunizing peptide

  • Expression controls: Compare tissues with known high versus low ATL8 expression

• Common artifacts and their resolution:

  • Autofluorescence: Identify through multi-channel imaging and spectral unmixing

  • Edge effects: Examine pattern distribution relative to tissue architecture

  • Fixation artifacts: Compare multiple fixation protocols

  • Non-specific binding: Optimize blocking conditions systematically

• Validation through complementary approaches:

  • Confirm patterns with ATL8-GFP fusion protein localization

  • Verify with subcellular fractionation followed by immunoblotting

  • Support with in situ hybridization for transcript localization

  • Compare with published expression data from similar conditions

• Quantitative assessment approaches:

  • Use digital image analysis with defined intensity thresholds

  • Perform colocalization analysis with known compartment markers

  • Apply unbiased stereological methods for pattern quantification

  • Implement machine learning algorithms for pattern recognition

These systematic approaches ensure that immunohistochemical findings represent genuine ATL8 localization rather than technical artifacts or non-specific signals.

How can researchers integrate ATL8 protein data with transcriptomic findings for comprehensive pathway analysis?

Integrating ATL8 protein-level data with transcriptomic information provides deeper insights into regulatory mechanisms:

• Correlation analysis approaches:

  • Compare ATL8 protein levels with mRNA expression under identical conditions

  • Identify potential post-transcriptional regulation when protein and mRNA levels diverge

  • Correlate with expression patterns of genes involved in BCAA catabolism that show coordinated regulation

  • Analyze time lags between transcriptional and protein-level changes

• Regulatory network reconstruction:

  • Identify transcription factors potentially controlling both ATL8 and co-regulated genes

  • Analyze promoter elements of coordinately regulated genes

  • Study the effects of SnRK1 signaling on both transcriptome and ATL8 protein levels

  • Map potential feedback mechanisms where protein degradation influences transcription

• Pathway enrichment integration:

  • Perform gene ontology analysis on genes co-regulated with ATL8

  • Identify biological processes enriched in both transcriptomic and proteomic datasets

  • Apply pathway analysis to position ATL8 within stress response networks

  • Use protein interaction data to connect transcriptional modules

• Visualization and modeling approaches:

  • Develop integrated network visualizations combining protein and transcript data

  • Create mathematical models predicting ATL8 dynamics based on multiple data types

  • Apply machine learning to identify patterns across multi-omics datasets

  • Implement Bayesian network analysis to infer causal relationships

This integration provides a systems-level understanding of how ATL8 functions within the broader context of plant stress response pathways, revealing both transcriptional and post-translational regulatory mechanisms.